Media
Articles
The Digital Reconstruction of Healthcare
By John Halamka, MD, MS Paul Cerrato
Although remote patient monitoring, machine learning, and artificial intelligence hold great promise for care delivery, there is limited high-value, evidence-based research on these issues. Technology will facilitate the transformation of care, but leaders need to exercise care in their strategy and execution…..
Redesigning COVID-19 Care With Network Medicine and Machine Learning
By John Halamka, MD, MS Paul Cerrato, MA Adam Perlman, MD, MPH
This review examines the network of interacting cofactors that influence the host-pathogen relationship, which in turn determines one’s susceptibility to viral infections like COVID-19. It then evaluates the role of machine learning, including predictive analytics and random forest modeling, to help clinicians assess patients’ risk for development of active infection and to devise a comprehensive approach to prevention and treatment……
Understanding the Role of Digital Platforms in Technology Readiness
By John Halamka, MD, MS Paul Cerrato, MA
State-of-the-art digital tools that take advantage of machine learning-derived algorithms and advanced data analytics have the potential to transform regenerative medicine by enabling investigators and clinicians to extract intelligence and actionable insights from published studies, electronic health records, pathology images and a variety of other sources. Used in isolation, however, these tools are not as effective as they can be integrated into a comprehensive strategy – a platform……
An FP’s guide to AI-enabled clinical decision support
By John Halamka, MD, MS Paul Cerrato, MA
To better understand the capabilities and challenges of artificial intelligence and machine learning, we look at the role they can play in screening for retinopathy and colon cancer…..
Setting the Stage for Next-Generation mHealth
By John Halamka, MD, MS Paul Cerrato, MA
Open the pod bay doors, HAL.… I’m sorry Dave, I’m afraid I can’t do that.” To this day, those lines from Space Odyssey 2001 still elicit fear in the minds of those who worry that computers will enslave humanity…….
Can You Make Your EHR Less Annoying?
By Paul Cerrato
Countless physicians complain that they spend so much time in front of their computers inputting information that they have little time to interact with patients…..
Reinventing CDS Requires Humility in the Face of Overwhelming Complexity
By John Halamka. MD
Paul Cerrato and I have created a new book, Reinventing Clinical Decision Support, our first to be published about Platform thinking….
VIDEOS
AI, Big Data are valuable assets to physicians
John Halamka, CIO of Beth Israel Deaconess Medical Center, and Paul Cerrato, Contributing Writer, Medscape, Medpage Today, discuss how AI and big data can help make personalized medicine a reality.
Machine Learning in Clinical Decision Support
In the final analysis, Baum et al. discovered that intensive lifestyle modification averted cardiovascular events for two subgroups, patients with HbA1c 6.8% or higher (poorly managed diabetes), and patients with well-controlled diabetes (Hba1c < 6.8%) and good self-reported health. That finding applied to 85% of the entire patient population studied. On the other hand, the remaining 15% who had well controlled diabetes but poor self-reported general health responded negatively to the lifestyle modification regimen.
The negative and positive responders cancelled each other out in the initial statistical analysis, falsely concluding that lifestyle modification was useless. The Baum et al. reanalysis lends further support to the belief that a one-size-fits-all approach to medicine is inadequate to address all the individualistic responses that patients have to treatment.
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